class_docstr: Assumes that weight update is done during backward pass,
  thus step() is a no-op.
class_docstr_tok: ["Assumes","that","weight","update","is","done","during","backward","pass",",","thus","step","(",")","is","a","no-op","."]
code: def __repr__(self) -> str:
      return optim.Optimizer.__repr__(self)
  
file_path: torchrec/torchrec/optim/fused.py
imports: import abc
  from typing import Any
  from torch import optim
  from torchrec.optim.keyed import KeyedOptimizer
label_desc: Use image node_id 3 for calling the FusedOptimizer obj's underlying member method code with example usage: obj.__repr__() and returns: optim